The aim of this systematic literature review (SLR) is to provide a comprehensive overview of
the current state of Windows malware detection techniques, research issues, and future …

This paper presents API-MalDetect, a new deep learning-based automated framework for
detecting malware attacks in Windows systems. The framework uses an NLP-based encoder …

Energy Harvesting (EH) as a power source plays a critical role in the advent of new
technologies such as the Internet of Things (IoT). But, by providing power within the …

Given their escalating number and variety, combating malware is becoming increasingly
strenuous. Machine learning techniques are often used in the literature to automatically …

Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …

Abstract The Internet of Things (IoT) has set the way for the continuing digitalization of
society in various manners during the past decade. The IoT is a vast network of intelligent …

The use of malware samples is usually required to test cyber security solutions. For that, the
correct typology of the samples is of interest to properly estimate the exhibited performance …

Blockchain represents a new promising technology with a huge economic impact resulting
from its uses in various fields such as digital currency and banking; malware represents a …

The Internet of Things (IoT) constitutes the foundation of a deeply interconnected society in
which objects communicate through the Internet. This innovation, coupled with 5G and …

Currently, enhancing the efficiency of vulnerability detection and assessment remains
relevant. We investigate a new approach for the detection of vulnerabilities that can be used …